Identification of Optimum Computational Protocols for Modeling the Aryl Hydrocarbon Receptor (AHR) and Its Interaction with Ligands

The aryl hydrocarbon receptor (AHR) is one of the principal xenobiotic receptors in living organisms and is responsible for interacting with several drugs and environmental toxins, most notably tetrachlorodibenzodioxin (TCDD). Binding of diverse agonists to AHR initiates an extensive set of downstream gene expression responses and thus identifies AHR among a key set of proteins responsible for mediating interactions between living organisms and foreign molecules. While extensive biochemical investigations on the interaction of AHR with ligands have been carried out, studies comparing the abilities of specific computational algorithms in explaining the potency of known AHR ligands are lacking. In this study we use molecular dynamics simulations to identify a physically realistic conformation of the AHR that is relevant to ligand binding. We then use two sets of existing data on known AHR ligands to evaluate the performance of several docking and scoring protocols in rationalizing the potencies of these ligands. The results identify an optimum set of protocols that could prove useful in future AHR ligand discovery and design as a target or anti-target. Exploration of the details of these protocols sheds light on factors operating in modeling AHR ligand binding.